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The Other January Effect: International Evidence

Author

Listed:
  • Martin T. Bohl
  • Christian A. Salm

Abstract

This paper investigates the predictive power of stock market returns in January for the subsequent eleven months' returns across 19 countries, thereby contributing to the literature on stock market seasonalities. Only two out of 19 countries' stock markets exhibit a robust Other January E ect. In light of this evidence, we conclude that the Other January E ect is not an international phenomenon.

Suggested Citation

  • Martin T. Bohl & Christian A. Salm, 2009. "The Other January Effect: International Evidence," CQE Working Papers 0809, Center for Quantitative Economics (CQE), University of Muenster.
    • Handle: RePEc:cqe:wpaper:0809
    as

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    File URL: https://www.wiwi.uni-muenster.de/cqe/sites/cqe/files/CQE_Paper/CQE_WP_8_2009.pdf
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    References listed on IDEAS

    as
    1. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 249-286, November.
    2. John Y. Campbell & Robert J. Shiller, 1988. "Stock Prices, Earnings and Expected Dividends," Cowles Foundation Discussion Papers 858, Cowles Foundation for Research in Economics, Yale University.
    3. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    4. Campbell, John Y. & Yogo, Motohiro, 2006. "Efficient tests of stock return predictability," Journal of Financial Economics, Elsevier, vol. 81(1), pages 27-60, July.
    5. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
    6. repec:bla:jfinan:v:43:y:1988:i:3:p:661-76 is not listed on IDEAS
    7. Keim, Donald B. & Stambaugh, Robert F., 1986. "Predicting returns in the stock and bond markets," Journal of Financial Economics, Elsevier, vol. 17(2), pages 357-390, December.
    8. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    9. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    10. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    11. Jensen, Gerald R. & Mercer, Jeffrey M. & Johnson, Robert R., 1996. "Business conditions, monetary policy, and expected security returns," Journal of Financial Economics, Elsevier, vol. 40(2), pages 213-237, February.
    12. Cooper, Michael J. & McConnell, John J. & Ovtchinnikov, Alexei V., 2006. "The other January effect," Journal of Financial Economics, Elsevier, vol. 82(2), pages 315-341, November.
    13. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    14. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    15. Sven Bouman & Ben Jacobsen, 2002. "The Halloween Indicator, "Sell in May and Go Away": Another Puzzle," American Economic Review, American Economic Association, vol. 92(5), pages 1618-1635, December.
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    More about this item

    Keywords

    Stock market efciency; Other January Efect; Stock market anomalies;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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